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JMLR Workshop and Conference Proceedings

Volume 45: Proceedings of The 7th Asian Conference on Machine Learning

Editors: Geoffrey Holmes, Tie-Yan Liu

Contents:

Preface

Preface

Geoffrey Holmes, Tie-Yan Liu

Accepted Papers

Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices

Inbal Horev, Florian Yger, Masashi Sugiyama

Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension

Ata Kaban

Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities

Hiroaki Sasaki, Voot Tangkaratt, Masashi Sugiyama

Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias

Yohei Kondo, Shin-ichi Maeda, Kohei Hayashi

A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections

Ata Kaban

Consistency of structured output learning with missing labels

Kostiantyn Antoniuk, Vojtech Franc, Vaclav Hlavac

Maximum Margin Partial Label Learning

Fei Yu, Min-Ling Zhang

Robust Multivariate Regression with Grossly Corrupted Observations and Its Application to Personality Prediction

Xiaowei Zhang, Li Cheng, Tingshao Zhu

Data-Guided Approach for Learning and Improving User Experience in Computer Networks

Yanan Bao, Xin Liu, Amit Pande

A Unified Framework for Jointly Learning Distributed Representations of Word and Attributes

Liqiang Niu, Xin-Yu Dai, Shujian Huang, Jiajun Chen

Preference Relation-based Markov Random Fields for Recommender Systems

Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang

Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach

Bin Li, Julia Yu, Jie Zhang, Bin Ke

Improving Sybil Detection via Graph Pruning and Regularization Techniques

Huanhuan Zhang, Jie Zhang, Carol Fung, Chang Xu

Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization

Yiu-ming Cheung, Jian Lou

Class-prior Estimation for Learning from Positive and Unlabeled Data

Marthinus Christoffel, Gang Niu, Masashi Sugiyama

Streaming Variational Inference for Dirichlet Process Mixtures

Viet Huynh, Dinh Phung, Svetha Venkatesh

Expectation Propagation for Rectified Linear Poisson Regression

Young-Jun Ko, Matthias W. Seeger

Curriculum Learning of Bayesian Network Structures

Yanpeng Zhao, Yetian Chen, Kewei Tu, Jin Tian

Continuous Target Shift Adaptation in Supervised Learning

Tuan Duong Nguyen, Marthinus Christoffel, Masashi Sugiyama

Surrogate regret bounds for generalized classification performance metrics

Wojciech Kotlowski, Krzysztof Dembczynski

Budgeted Bandit Problems with Continuous Random Costs

Yingce Xia, Wenkui Ding, Xu-Dong Zhang, Nenghai Yu, Tao Qin

Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation

Tingting Zhao, Gang Niu, Ning Xie, Jucheng Yang, Masashi Sugiyama

Statistical Unfolded Logic Learning

Wang-Zhou Dai, Zhi-Hua Zhou

Integration of Single-view Graphs with Diffusion of Tensor Product Graphs for Multi-view Spectral Clustering

Le Shu, Longin Jan Latecki

Autoencoder Trees

Ozan Irsoy, Ethem Alpaydn

Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models

Adepu Ravi Sankar, Vineeth N Balasubramanian

One-Pass Multi-View Learning

Yue Zhu, Wei Gao, Zhi-Hua Zhou

Largest Source Subset Selection for Instance Transfer

Shuang Zhou, Gijs Schoenmakers, Evgueni Smirnov, Ralf Peeters, Kurt Driessens, Siqi Chen